High-precision cognitive performance test battery suitable for internet and non-internet use

ABSTRACT

A system and method for internet-based cognitive performance measurement is provided. Furthermore, a method is provided whereby improvements in statistical accuracy is obtained.

TECHNICAL FIELD

The present invention relates generally to a system and method forinternet-based cognitive performance testing.

BACKGROUND OF THE INVENTION

Systems and methods for computer based testing (CBT) are known to theart. For example U.S. Pat. No. 5,827,070 to Kershaw et al. discloses CBTmeans for administration of standardized test, e.g. SATs, LSAT, GMATs,etc. The system and method of Kershaw et al. does not depend on thespeed and accuracy of the individual examinee's keystroke responses tothe test stimuli. Lewis et al. (U.S. Pat. No. 5,059,127) disclose acomputerized mastery testing system providing for the computerizedimplementation of sequential testing. This disclosure also does notrelate to the speed and accuracy of the individual examinee's keystrokeresponses to the test stimuli. Swanson et al. (U.S. Pat. No. 5,657,256)disclose a method and apparatus for administration of computerizedadaptive tests. Swanson is similarly unconcerned about the examineeresponse time.

When people measure their response time, recall or other cognitiveskills using computer-based test systems, they typically press number orletter keys (or keys representing other symbols like circles andsquares) in response to visual or auditory or other sensory signalspresented to them. The average time they take to press the correct keysis their response time.

This type of measurement is subject to a number of errors that makeresponse time results relatively imprecise. The effects of recent foodsand beverages, medicines, amount of sleep and other factors that affectalertness or drowsiness all influence response speed and accuracy, sothat measurements on any single day may not represent actual averageperformance level.

A key source of measurement error is change in motivation to respondquickly. One day a person may try quite hard to reduce their responsespeed. The next day they may relax and perform more slowly simplybecause they care less about their “score” that day. Typically the errorrate increases (incorrect responses are made more frequently) whenpeople try harder to react quickly. Investigators commonly measure errorrate to determine the “response speed/accuracy tradeoff” for each personor group of people.

While the response speed/accuracy tradeoff is usually discussed inconnection with relatively simple responses, a similar tradeoff canoccur during memory measurements when speed is only a secondaryconsideration. Response speed is intrinsically linked with recallaccuracy because transient memory traces fade if the response (e.g.typing a list of words) is not completed rapidly.

Response speed may also vary from second to second and minute to minuteas a result of boredom with the test, short-term fatigue from repeatedmotion, eye strain from staring at the computer screen, and stimuluspatterns that confuse the user and cause response errors. Differenttypes of transitions such as shifts between responses involving one handand the other, or one finger and the corresponding finger on the otherhand, can also affect response speed and accuracy for individualresponses.

All of these factors together make precise performance measurement allbut impossible. Even under controlled laboratory conditions, thecorrelation between test scores on one occasion and scores by the sameindividuals at a later time, averages only 0.63 (Salthouse & Babcock,1991; Lowe & Rabbitt, 1998; Versavel et al., 1997; Wetherell, 1996). Inother words, performance results can vary by plus or minus 20% from oneday or week to the next.

The correlation between test results on separate days, called“test-retest reliability,” is perhaps the most widely used indicator ofmeasurement reliability. The average value of 0.63 has not changedappreciably during the last two decades, indicating that attempts toimprove measurement reliability have generally met with little success.

Perhaps the best way to describe the need for measurement precision, andthe need for this invention, is to discuss the circumstances of anindividual who participated in a recent study to determine whetherblueberries can reduce multiple sclerosis symptoms (Pappas et al.,2001).

SF is one of hundreds of thousands of people in the U.S. who havechronic, neurodegenerative diseases for which there is no cure. Hecannot drive and cannot find work because his coordination and memoryare affected. He must sell the home he, his wife and children live inbecause they need the money for his medical and dental expenses. Hisrelatively expensive medicines give no apparent benefit. The medicinesdo however dry his mouth and cause his teeth to crack, causing him tolose three teeth during the last several months. Concerned about hisdental bills, SF asked his dentist to remove his remaining teeth so hewould not have to pay to have them repaired when he would lose themanyway. (His dentist refused.) His physician advised him to take arecommended performance test battery just once a year because he cannotafford the cost of more frequent evaluations. He must therefore wait forvery long periods of time before obtaining objective evidence that hismedications are or are not helping him—time he can ill afford since hisdisease is growing steadily worse. And of course after such long waitingperiods, any performance benefits provided by his medications may becancelled by the steady decline from his chronic illness.

SF can expect to decline at a rate which reduces his performance scoresby roughly 4% to 10% each year. If his medicines are effective, hisannual decline may be decreased by half a percentage point or perhapsseveral percentage points—however he most probably cannot measure thisbenefit because once-a-year testing is not accurate enough to measurechanges smaller than 5%. Once-a-year testing will always be incapable ofmeasuring changes of 5% or less simply because he may perform 5% or 10%better or worse than his average on the day when measurement isperformed.

So the test results for which SF must wait so long, and pay so much for,are largely worthless to him and his physician since they will not beprecise enough to indicate whether his medicines helped him.

SF clearly needs, and many thousands of other people in similarcircumstances need, a test system that is accurate to within 1% or 2% sothat effective treatments can be identified. He also needs a measurementsystem that is far less expensive than that recommended by hisphysician, so that he can obtain results many times each year. And heneeds a test that can be taken at home, so that he is spared the effortand/or the cost of transportation to a test center.

For these and many other reasons, there is a clear need for increasedmeasurement precision

One strategy used by scientists seeking greater precision is to reduceresponse time variability by discarding high and low responses withineach test or test series. For example, the slowest half and the fastestquarter of response times may be discarded from each 30 seconds oftesting, and the average of the remaining data obtained.

This type of data trimming certainly reduces variability—but it alsoreduces the amount of useable data and therefore reduces measurementprecision, which is related to the amount of data. (As a general rule,precision is directly proportional to the square root of the number ofdata points, if approximately random variation is the cause ofimprecision.)

Discarding high response times also prevents or sharply reduces theaccuracy with which benefits or harm from different health strategiescan be measured if performance changes occur primarily within theresponse times that are discarded. This occurred recently during anDanbury MS Blueberry Study (Pappas et al, 2001). Very slow responsetimes were markedly reduced after blueberry consumption for many studyparticipants, however this was not evident from trimmed data sets, fromwhich all slow responses had been removed. Only when raw data wasexamined did the principal investigator see this benefit.

Scientists have also attempted to reduce measurement error by reducingpractice effects that occur when examinees take the same or similartests repeatedly. Gradual improvement due to practice is different foreach individual and even for each type of response for each individual.Such gradual improvement can mask benefits of medication or other healthstrategies, or can mask harm due to exposure to pollutants, fatigue,etc.

To reduce practice effects, investigators have asked examinees to taketests many dozens of times, so that the learning period can be passedand further improvement due to practice will not occur. Thispractice-until-no-more-improvement-occurs strategy was not generallysuccessful since improvement typically occurs over hundreds or eventhousands of responses. This strategy is of course impractical forpeople like SF when the expense and effort of travel and testing arehigh. There is a clear need for test methods that reduce or eliminatepractice effects.

Measurement precision and test-retest reliability has for the most partbeen ignored by inventors interested in reaction time and memorymeasurement. Only two previously patented performance measurementmethods related to “reaction time” have explicitly addressed the issueof test-retest reliability and measurement precision. None haveevidently attempted to determine the precision with which response timemeasurements are made.

Wurtman (1984) obtained a test-retest reliability of 0.65-0.74 whenevaluating an amino acid mixture for improving vigor and mood in normalhuman patients, however the method used to obtain this test-retestreliability was not the subject of his patent.

Using an electroencephalogram-based, computer-aided training method and4 examinees, Gevins et al (1998) obtained an average “test setclassification” of 95% (range 92%-99%) calculated by a trainedpattern-recognition network. Their “test-retest reliability” computationalgorithm apparently had little to do with the (Pearson) correlationcoefficient commonly used to determine test-retest reliability values.Their use of the phrase “test-retest reliability” illustrates thedifficulty that can arise when a term used to define measurementprecision is given different meanings by different investigators.

Rimland (1988; U.S. Pat. No. 4,755,140) describes a hand-held reactiontime test but does not determine either test-retest reliability or theprecision with which reaction time is measured. His device that employsno signal sequence restrictions and other apparent methods for improvingprecision.

Reynolds et al. (1999; U.S. Pat. No. 5,991,581) developed an interactivecomputer program for measuring mental ability that automatically adjuststask complexity and selects letters or symbols with equal probability.No discussion of performance measurement precision or test-retestreliability is provided, and there is no determination of the precisionwith which response time measurements are made.

Buschke (1988; U.S. Pat. No. 4,770,636) describes a memory monitor thatproduces challenge signals 7 or 10 digits in length. He mentions nosignal sequence restrictions that might improve measurement precision.His choice of 7 or 10 digit sequences quite likely results infrustration for individuals who cannot handle such long numbers andreduced precision for individuals who can handle 10 digits readily. Hisuse of punctuation after three-digit segments within these longersequences appears to be a step in the right direction since it willpromote consistent “chunking” of signals within and between data sets.

Buschke's 1993 “cognitive speedometer” (1993; U.S. Pat. No. 5,230,629)involves relatively sophisticated control measurements but also does notdetermine measurement precision or employ signal-sequence restrictions.He does attempt to control the speed-accuracy ratio by keeping errorsbelow an upper limit but does not ask examinee's to proceed quicklyenough to make at least a minimum number of errors. This allowsconsiderable response speed variability since examinee's may relax orproceed with greater vigor from time to time, without ever exceeding oreven approaching his permitted level of errors.

Perelli (1984; U.S. Pat. No. 4,464,121) has developed a portable devicefor measuring fatigue effects that he did not determine test-retestreliability or measurement precision. He does however increase precisionby blocking challenge signal repetition. No two signals in a row can beidentical. His motivation for this restriction was not to improvemeasurement precision but to clearly indicate each new trial.Nevertheless his restriction is important since it removes trials wherethe signal is the same as that just presented, and therefore preventsexaminees from responding more quickly to such signals than to othersand therefore reduces variability among response times and increasesmeasurement precision. He also does not encourage examinees to proceedquickly enough to make a minimum acceptable number of errors andtherefore allows more response speed variability than optimal.

Keller's response speed and accuracy measurement device (1992; U.S. Pat.No. 5,079,726) also does not allow the same digit twice in a row withineach 5 digit signal, and several other restrictions are also imposed.5-digit signals cannot begin with the number 1. Adjacent sequentialdigits are forbidden. And no digit may be used twice within the same5-digit signal. He does not however place any restrictions on thefrequency of digits or transitions between digits over a series ofsignals. Thus he permits one digit, say the number 2, to appear adisproportionate amount of the time during a series of measurements. Ifan examinee is especially fast or slow when pressing 2, his or heraverage response times will be reduced or elevated in comparison toother measurement sessions, response time variability will be increasedand measurement precision will be decreased. He makes not effort tolimit error rates to maximum or minimum levels and does not determinethe precision with which response times are measured.

There exists a need to eliminate computer delay as a source of error.Virtually all computers have hidden “background” processes that occurfrom time to time and compete with resources required for accurate timemeasurement. The problem is particularly severe in the most powerful,modem computers, which have large numbers of background processes. Everyseveral minutes, one or another task is undertaken that delays responsetime measurement by approximately 5% or more—enough to increasemeasurement variability beyond the accuracy needed for preciseassessment of medical benefits or performance effects from otherpotentially dangerous or life-saving activities, events or conditions.If several competing programs are active when measurement is made, asmuch as 100% of the computers central processing unit (“CPU”) time maybe occupied, possibly for as long as or longer than several seconds.

FIG. 1 shows a screen shot of CPU usage in the absence of user-initiatedactivity obtained from a 200 MHz Windows NT 4 Gateway computer.Periodic, transient demands on CPU capacity are evident, including onerelatively unusual spike up to 100% of CPU capacity that lasted severalseconds before receding.

During the recent Danbury MS Blueberry Study (Pappas et al., 2001), wheninterference from background activities was measured before eachkeystroke during choice reaction time testing, occasional interferencewas recorded for all study participants, and most had potentiallysignificant interference clusters from time to time (FIG. 2).

Performance results obtained during this past year during the Danbury MSBlueberry Study indicate that measurement error was limited to 1% or 2%(test-retest reliability was 0.991) and that practice effects werenegligible when testing (and therefore practice) was limited to 2minutes each week (FIGS. 3 and 4). Analysis of response times obtainedafter interference was detected indicates that apparent response timesincreased by roughly 7%, depending on the severity of the interference.This 7% error is large enough to a serious concern, but not so largethat it cannot be reduced to insignificance by frequent (twice persecond) precision checks and rejection of questionable data.

The precision improvement methods described in this patent applicationand employed during the Danbury MS Blueberry Study controlledmeasurement variability to a greater extent than expected and alloweddata sets for individual participants to be split into separateperformance measures for each finger used during response time testing.FIG. 4 contains a typical single-finger data set for one of the studyparticipants. The steady, parallel changes observed for each fingerindicate that measurement precision was quite sufficient for this typeof single-finger monitoring.

A thorough search of prior art has indicated that average measurementprecision among 77 different published performance tests wassurprisingly low. Test-retest reliability was only 0.63. Resultsobtained this past year using the methods described herein yielded atest-retest reliability of 0.991. Accordingly, there exists a need for amethod for increased measurement precision.

SUMMARY OF INVENTION

The present invention provides a computer based system for testing thecognitive performance of at least one examinee comprising: comprising:at least one source network entity (SNE) having machine readableinstructions, at least one test development system, local memory, and aplurality of executable files stored in said memory; a data distributionsystem (DDS) logically connected to said source network entity; and atleast one destination network entity (DNE), having local memory,logically connected to said data distribution system.

The present invention provides a system for internet-based testingcomprising a plurality of subsystem including: a test developmentsystem; a data distribution system; a workstation; a workstationcalibration system; an examinee monitoring system; and an examineemotivation system.

According to an aspect of the present invention, a test developmentsystem is provided. The test development system comprises a digitalcomputer provided appropriate software such as an operating system andmeans for generating digital representations of challenge signals to bepresented to an examinee. Signals may be numbers, letters, words, othersymbols, sounds or combinations of these and/or other response triggers.The signals may be presented singly or in any combination of theplurality of possible signals. The test development system furthercomprises appropriate software, databases and digital storage means. Thetest development system provides a definition file defining specificinformation said test development system requires and a format in whichsaid specific information is to be provided, at least one examineeinformation file, at least one examinee response file.

According to an aspect of the invention, the test development system islogically connected, in computer fashion to data transmission means.Such a connection may be for example a modem or cable modem connectionto the internet. In such case the data transmission means comprise theinternet.

According to an aspect of the present invention, a data distributionsystem is provided. The data distribution system

According to an aspect of the present invention a computer based methodfor testing the cognitive performance of at least one examinee isprovided. The method comprises the steps of:

-   -   (a) providing a computer based testing system comprising: at        least one source network entity (SNE) having machine readable        instructions, at least one test development system, local        memory, and a plurality of executable files stored in said        memory; at least one data distribution system (DDS) logically        connected to said source network entity; at least one        destination network entity (DNE) logically connected to said        data distribution system, wherein said DNE has local memory;    -   (b) generating a computer signal train comprising said at least        one set of instructions, said at least one test development        system and said plurality of executable files and transmitting        said computer signal train to said data distribution system;    -   (c) embodying said computer signal train in a carrier wave using        said data distribution system;    -   (d) distributing said carrier wave embodying said computer        signal train to said destination network entity;    -   (e) displaying general and motivational instructions to said        examinee;    -   (f) obtaining information relating to examinee health history        and cacheing said information in DNE memory;    -   (g) calibrating said destination network entity, wherein said        calibration is performed iteratively prior to each response;    -   (h) displaying at least one softshifted challenge signal;    -   (i) measuring at least a first cognitive performance of said        examinee, wherein said measurement is bounded by pre-determined        error limits;    -   (j) providing performance feedback to said examinee;    -   (k) providing motivational feedback to said examinee; and    -   (l) providing summary information to said examinee.

According to an aspect of the invention, a computer-based performancemeasurement system is provided that provides more precise results thanpreviously available, for at least some measures of performance.

According to an aspect of the invention means are provided for obtainingmore precise performance data than previously possible, so people,and/or their physicians, can determine how to improve their health, sothat scientists can conduct more precise performance research, and sothat other people interested in their performance can obtain morereliable, more convenient and more affordable performance measurements.

An aspect of this invention is the linked storage of informationabout 1) performance, 2) computer measurement accuracy, 3) health and 4)health-related activities and events, including foods, beverages andmedications consumed, exercise, sleep, social events and any activity orevent that may possibly affect health or performance. Storage may be inone or more data files but must be accomplished to enable information ineach of these four categories to be linked together so that logicalconclusions can be reached. A key aspect of the information stored ineach category is the date and time of each measurement, aspect ofhealth, activity or event.

Time stamps allow performance results to be rejected or corrected ifmeasurement precision calibration results obtained immediately before orafterward raise doubts about measurement accuracy at that time. Computermeasurement error typically occurs when other background processes(“interference”) prevent timely execution of the measurement softwarecommands. Such interference usually occurs for relatively short periodsof time, so performance data can be rejected if it was obtained atapproximately the same time interference was detected. Rejecting justsome data while keeping results obtained when calibration results aresatisfactory allows more data to be used and therefore increasesmeasurement precision, even for computers subject to relatively highlevels of transient background interference.

Time stamps also allow performance, health and health activityinformation to be related.

According to an aspect of the invention, changes in examinee responsetime and short-term memory are measured. Changes in examinee responsetime and short-term memory may have important medical-diagnostic value,indicating for example local areas of hypoxia (low oxygen) or othertransient or progressive health problems, and may provide a relativelyprecise measure of the effectiveness of different doses and combinationsof medications and health supplements for the individual examinee.

A further aspect of the invention provides measures of cognitiveperformance having precision sufficient to measure changes in theperformance of individual examinees, rather than just changes amonggroups of examinees.

According to an aspect of the invention, means are provided for relatingingestion of dietary components or supplements, medications or otherdrugs, or alcohol to changes in cognitive performance.

According to an aspect of the invention, means are provided forincreasing the number of performance measurements obtained per unit timeper examinee and means are provided for increasing the precision ofthose measurements. Therefore, also is provided means to decreaseproportionately the cost of long-term experiments and to enable researchprotocols that otherwise would be too expensive to be funded.

According to an aspect of the invention, a response time measurementsystem is provided that instructs users to remain above a minimum errorrate and/or specifies a relatively narrow range of recommended errorrates.

According to an aspect of the present invention, methods for reducingmeasurement error are applied to virtually any computer-basedperformance measurement system, whether the challenge signals comprisenumbers, letters, words, other symbols, sounds or combinations of theseand/or other response triggers or whether single responses or a seriesof different responses are required.

According to an aspect of the present invention, methods are providedapplicable to a variety of response time measurements (such as simpleand choice response time, digit-symbol substitution tests and memoryscanning tests) and also to memory measurements (such as number recall,word recall and word pair recall).

According to an aspect of the present invention, use of the Internet forrepeated and more precise performance measurement may provide scientistswith both an opportunity and a previously missing spark for developmentof global standards for performance tests that will speed many differentareas of health research.

Still other objects and advantages of the present invention will becomereadily apparent by those skilled in the art from the following detaileddescription, wherein it is shown and described preferred embodiments ofthe invention, simply by way of illustration of the best modecontemplated of carrying out the invention. As will be realized theinvention is capable of other and different embodiments, and its severaldetails are capable of modifications in various obvious respects,without departing from the invention. Accordingly, the description is tobe regarded as illustrative in nature and not as restrictive.

BRIEF DESCRIPTION OF DRAWINGS

FIG. 1 is screen shot showing central processing unit usage for aWindows NT 4.0 200 MHz Gateway 2000 computer in the absence ofuser-initiated activity occurred,

FIG. 2 is a graph of percent measurement error for one of theparticipants during the Danbury MS Blueberry Study,

FIG. 3 shows the test-retest reliability of choice reaction timemeasurements during the Danbury MS Blueberry Study,

FIG. 4 contains choice reaction time results for one of the BlueberryStudy participants,

FIG. 5 is a flow chart outlining instructions presented to examineeprior testing,

FIG. 6 is a flow chart outlining signal generation, computercalibration, and feedback,

FIG. 7 is a flow chart outlining keystroke capture, processing, andfeedback,

FIG. 8 is a flow chart outlining data storage, processing, and feedback,

The invention is best understood from the following detailed descriptionwhen read in connection with the accompanying drawing. It is to benoted, however, that the appended drawings illustrate only typicalembodiments of this invention and are therefore not to be consideredlimiting of its scope, for the invention may admit to other equallyeffective embodiments.

DETAILED DESCRIPTION OF A PREFERRED EMBODIMENT

Reference is made to the figures to illustrate selected embodiments andpreferred modes of carrying out the invention. It is to be understoodthat the invention is not hereby limited to those aspects depicted inthe figures.

The unique methods that make the performance measurement systemdescribed in this application effective are a combination of measurementerror reduction methods and variability monitoring systems designed toreduce sources of variation in response speed and response accuracy thatoperate from one fraction of a second to the next, one second to thenext, one minute to the next, one day to the next, and even one week,month and year to the next.

The intent is not only to reduce measurement variation that occurs insubsecond to monthly and yearly cycles but to monitor the variation ateach time scale and make immediate announcements to the user, withineach measurement session, to ensure that all sources of variability andmeasurement error are within acceptable boundaries or at least that allpossible adjustments are made to minimize sources of measurementvariation the moment they are detected.

To reduce measurement error due changes in alertness or drowsiness orchanges in motivation to respond rapidly (e.g. to match or beat previousscores) for any reason, measurements are obtained with repeated feedbackconcerning past and present response times and error rates, so thatpeople taking measurements can see even within each series of responseswhether they are performing as quickly and as accurately as they werebefore. They can quickly adjust to match previous response speeds anderror rates even before a significant portion of the present test serieshas passed, so that much more reliable results (at consistent errorrates) are obtained.

If users cannot reduce response times to match those obtained previouslybecause they are in fact slower during the present measurement session,they invariably try harder and their error rate increases, so thatdifferent points on the speed/accuracy tradeoff curve are exploredwithin each measurement session. Trying different speeds and errorrates, back and forth until previous error rates are matched, withexplicit instructions that error rates should never be less than aminimum or greater than a maximum, essentially ensures that at leastsome data are obtained during past and present measurement sessions withthe same or very similar degrees of accuracy. Much more precisecomparison of past and present results is consequently possible.Concentration, alertness, determination to succeed typically risesharply when users realize they are not performing up to par—sodecrements due to reduced alertness are overcome and differences fromprevious sessions are reduced.

To reduce measurement error due to factors that vary from day to day,week to week and month to month, results from previous measurementsessions are displayed as a graph or bar chart several times during eachmeasurement session so that response speed and error rate can beadjusted to approximate response times achieved weeks or months earlier.Display of previous results several times during each session allowscorrective adjustment to occur repeatedly before the measurement sessionis completed.

To reduce measurement error due to eye strain, fatigue and boredomwithin each measurement session, each session is interrupted severaltimes and data from the present and previous measurement sessions aregraphed, percentage changes, standard deviations and error rates aredisplayed, and statistical significance of changes is calculated.Several types of warnings are also displayed if response time has slowedsignificantly in comparison with previous results. Delays while data aredisplayed after each 10 to 15 seconds of testing serve as important restperiods, for hands, fingers, eyes and those parts of the brain that maybecome fatigued after repeated use.

To reduce measurement error due to second by second and minute by minutechanges other than fatigue, measurements are obtained over severalminutes during each test session and pooled to obtain a morerepresentative score for each test session.

To reduce response time measurement error due to short-term changes inspeed and accuracy from confusing patterns of signals and other factorsthat change every several seconds, signal images are presented sorapidly and responses are triggered and measured so rapidly (two or moretimes per second) that changes in response speed and error rate aredetected within seconds, testing is interrupted and correctiveinstructions can be displayed. Corrective messages allow individuals tochange their speed and/or error rate so that they remain within lowerand upper acceptable limits.

To reduce error due to repeated signals or to exceptionally common ormemorable (“salient”) signal patterns, the probability that the samesignal or salient signal patterns will be chosen more than once in a rowis reduced but not entirely eliminated. This probability reductiondecreases response time variation due to signal repetition and salientsignal patterns, but does not allow the user to rule out the possibilityof repetition and anticipate and execute unusually rapid responses basedupon anticipation.

Two examples will clarify the importance of reducing the occurrence ofrepeated signals and salient signal patterns:

EXAMPLE 1

Two series of signals, chosen randomly, are presented during consecutive“choice response time” measurement sessions: 1, 1, 2, 2, 3, 3 and 4, 2,1, 4, 3, 2. The correct response is to press the same key (1, 2, 3 or 4)as the signal. The first series almost invariably yields significantlylower response times because the same finger is used repeatedly and isprimed for more rapid responses after the first use.

EXAMPLE 2

During a number recall experiment, two series are presented: 1, 2, 3, 4,4, 4 and 8, 2, 5, 1, 6, 9. The first is much easier to recall because ofthe obvious pattern, enabling users who normally cannot recall 6-digitseries to score higher than their usual maximum of 5 digits. Each ofthese examples may seem far-fetched but in practice salient patternsappear quite frequently even when signals (numbers) are selectedrandomly, and they can cause quite noticeable performance shifts ifrelatively few responses are performed.

Most performance investigators present so many trials—in some casestesting subjects for hours—that the effect of occasional salient signalpatterns is negligible. However the goal of the invention described hereis to obtain precise results within very brief periods of measurement.So it is quite important to control variation due to salient signalpatterns. Brief measurement sessions are critical if users are to returnfrequently for measurements at different points in their personalperformance cycles—so that day-by-day changes in performance do notcause errors when monthly or yearly cycles are being monitored.

Simultaneously preventing measurement error due to repeated signals orsignal patterns like 1, 2, 3 . . . that lead to anticipation of oneresponse—and avoiding changes in anticipation when users realizesubsequent signals cannot occur, reduces two kinds of measurement error:response times are typically lower than average if the anticipatedsignal in fact occurs, and response times are typically longer if theanticipated signal does not occur.

Reducing the occurrence of unusually rapid responses, and also slowerthan average responses has the effect of reducing the standard deviationof a series of responses and making response time measurementsignificantly more precise. Reducing response time standard deviation(or any other measure of response time variation) enables small averagedifferences in response time from one session to the next, or one day orweek or month to the next, to be measured with much greater statisticalconfidence after shorter periods of measurement.

Evaluating the accuracy of measurements made by each computer:

-   -   To reduce measurement error due to day-by-day and        second-by-second changes in computer performance and the        accuracy with which each individual computer measures response        time, computer measurement error is determined after each        response is made, throughout each test session, and testing is        interrupted if measurement error ever exceeds an acceptable        upper limit. Instructions advise the user to close other        programs that may slow computer command execution, or to phone a        webmaster or other test supervisor for further advice concerning        computer performance.        Gathering More Data:

To enable more data to be gathered during each brief measurementsession, carefully chosen scoring rules have been developed. Forexample, the score for the day during a number recall session is definedin advance as the longest length number series that is recalledcorrectly three times in a row. To achieve a score of 9 for example, theuser must correctly recall three different 9-digit numbers withoutmaking any errors in between. As people try to recall longer numbers andreach their limit for the day, errors become more frequent until it isnot possible for them to recall three in a row. The only way to find outif they can recall three in a row is for users to try repeatedly,generating more data with each attempt, until they are convinced theycannot recall that length number three times in sequence and end themeasurement session. Actual scoring by research scientists analyzing thedata may involve computing the percentage correct at each users upperlimit, however stating a simple, clear goal of three in a row, is easierfor users to understand and aim for. For some people who are relativelyimpatient or older and more subject to fatigue, a score based ontwo-in-a-row may be best.

Computer Accuracy:

Computer measurement accuracy must by consistent from each measurementsession to the next if results are to be precisely compared acrosssessions. To ensure that each computer is functioning properlythroughout each measurement session, a standard set of computer commandsare executed and timed after every keystroke, the performance-timemeasurements are stored and averaged, and the average for each series ofaccuracy measurements is displayed, so that even transient interferencefrom other computer activities can be seen immediately. Testing isinterrupted and automatic warnings appear if accuracy is not sufficienteven for a single accuracy measurement, so that interference can beremoved or the data set discarded. The warnings advise the user to closeother programs that may slow computer command execution, or to phone awebmaster or other test supervisor for further advice concerningcomputer performance.

Simplest Versions:

For people with disabilities that prevent them from seeing or pressingindividual keys, a version of the response time program was preparedthat allows any key to be pressed when a large X is presented. Toprevent users from anticipating the signal, there is a variable responsetime prior to signal presentation for this version of the response timetest.

For people with no computer experience, a version has been prepared thatrequires only that the computer be turned on. The program is launchedautomatically and begins presenting signals without requiring anystart-up keys to be pressed. The session ends when the computer isturned off.

To the best of my knowledge, no other computer program starts withouteven requiring “Begin” or “Start” to be pressed.

Description of Data Records

A unique aspect of this invention is the linked storage of informationabout 1) performance, 2) computer measurement accuracy, 3) health and 4)health-related activities and events, including foods, beverages andmedications consumed, exercise, sleep, social events and any activity orevent that may possibly affect health or performance. Storage may be inone or more data files but must be accomplished so that information ineach of these four categories is linked together so that logicalconclusions can be reached. A key aspect of the information stored ineach category is the date and time of each measurement, aspect ofhealth, activity or event recorded by the examinee before eachperformance measurement session.

Time stamps allow performance results to be rejected or corrected ifmeasurement precision calibration results obtained immediately before orafterward raise doubts about measurement accuracy at that time. Computermeasurement error typically occurs when other background processes(“interference”) prevent timely execution of the measurement softwarecommands. Such interference usually occurs for relatively short periodsof time, so performance data can be rejected if it was obtained atapproximately the same time interference was detected. Rejecting justsome data while keeping results obtained when calibration results aresatisfactory allows more data to be used and therefore increasesmeasurement precision, even for computers subject to relatively highlevels of transient background interference.

Time stamps also allow performance, health and health activityinformation to be analyzed so that the most and least beneficialactivities can be identified.

According to an aspect of the invention, changes in examinee responsetime and short-term memory are measured. Changes in examinee responsetime and short-term memory may have important medical-diagnostic value,indicating for example local areas of hypoxia (low oxygen) or othertransient or progressive health problems, and may provide a relativelyprecise measure of the effectiveness of different doses and combinationsof medications and health supplements for the individual examinee.

A further aspect of the invention provides measures of cognitiveperformance having precision sufficient to measure changes in theperformance of individual examinees, rather than just changes amonggroups of examinees.

According to an aspect of the invention, means are provided for relatingingestion of dietary components or supplements, medications or otherdrugs, or alcohol to changes in cognitive performance.

According to an aspect of the invention, means are provided forincreasing the number of performance measurements obtained per unit timeper examinee and means are provided for increasing the precision ofthose measurements. Therefore, also is provided means to decreaseproportionately the cost of long-term experiments and to enable researchprotocols that otherwise would be too expensive to be funded.

According to an aspect of the invention, a response time measurementsystem is provided that instructs users to remain above a minimum errorrate and/or specifies a relatively narrow range of recommended errorrates.

According to an aspect of the present invention, methods for reducingmeasurement error are applied to virtually any computer-basedperformance measurement system, whether the challenge signals comprisenumbers, letters, words, other symbols, sounds or combinations of theseand/or other response triggers or whether single responses or a seriesof different responses are required.

According to an aspect of the present invention, methods are providedapplicable to a variety of response time measurements (such as simpleand choice response time, digit-symbol substitution tests and memoryscanning tests) and also to memory measurements (such as number recall,word recall and word pair recall).

According to an aspect of the present invention, use of the Internet forrepeated and more precise performance measurement may provide scientistswith both an opportunity and a previously missing spark for developmentof global standards for performance tests that will speed many differentareas of health research.

A minimal embodiment of the invention comprises a source network entity(SNE), a destination network entity (DNE), and a data distributionsystem (DDS) logically connecting the network entities. The networkentities may be, as a non-limiting example, PC computers. In a simpleembodiment, the SNE and the DNE may be the same physical device. In suchexample, the data distribution system comprises the internal data bus.

In a second, non-limiting example, the SNE is a network server and theDNE is a PC or workstation computer. In such example, the DDS is theinternet. The DDS may be embodied as a local area network (LAN), or asan extranet.

The DDS in principle is any medium capable of distributing computerreadable information. Thus the DDS may comprise an appropriatelyformatted diskette.

Either or both network entities may be embodied as any computationaldevice such as, for non-limiting example, a Palm Pilot.

The steps of a preferred embodiment of the inventive method is presentedwith reference to the flow diagrams of FIGS. 3-5, the step numbers andtitles refer to the numbered and titled boxes within the variousfigures.

Step 1: Display Instructions.

The source network entity (SNE) causes a digital image of testdevelopment system (TDS) to be embodied within a carrier wave and passedthrough the data distribution system (DDS) to the destination networkentity (DNE). The DNE executes the instructions, including a sessionadministration routine, comprising portions of the TDS. The Examineereceives instructions regarding the appropriate administration of thesession. Appropriate instructions are retrieved from an instructiondatabase by the session administration routine and displayed to theexaminee.

This step is critical for measurement precision because examinees areinstructed to make use of response time and error rate informationduring and throughout each measurement session and to maintain amore-or-less steady error rate so that results can be more preciselycompared from one session to the next. Users are also told how to placetheir fingers directly over appropriate keyboard or other response keysso that they do not subsequently discover that a different fingerplacement improves their response time. They are instructed to use anyof three alternative finger positions—including two intendedspecifically to be more comfortable for users with narrower and withwider fingers. Examinees are instructed to take whatever measures arenecessary to obtain steady results—e.g. to test themselves until theyhave passed the rapid learning phase or “practice period” and haveachieved a steady baseline, to obtain measurements at the same time ofday, and to refrain from caffeine or alcohol consumption, etc.

Measurement system users who are instructed properly are less likely todiscover, perhaps unwittingly or unconsciously, better strategies thatchange their response time and make results less consistent and lessreliable. Users are also more likely to adjust their response speed anderror rates more frequently if instructed to check several times duringeach measurement session and to use the response time and error rateinformation provided to adjust their response speed and error rateduring the remainder of the measurement session so that they remainwithin a consistent, limited range.

Use of lower and upper error limits specifying a narrow range (ratherthan a broad range) ensures that users will frequently fall outside therecommended range and will make speed adjustments that will produce dataon either side of the optimum error rate, so the average error rateremains consistent and response time data is more reliable. A singlerecommended error rate is not equivalent to a narrow acceptable range,since users will grow to accept error rates that are too high and toolow and will make up their own personal ranges of acceptability that maychange with time or mood and be less reliable than a specifiedacceptable range.

Alternative finger placements are provided so that users with largefingers need not squeeze their fingers together, ignore the discomfortwhile testing, and overcome the friction caused by squeezing. Morecomfortable finger placement frees users from this distraction andimpediment to rapid responses and allows them to respond morereproducibly and reliably. A preferred embodiment employs at least twosets of alternative finger positions. In a preferable embodiment of theinvention, test subjects are instructed to adopt the standard “qwerty”finger position, i.e., “asdf ;lkj.” The inventive method contemplatesacceptable alternative finger placements using adjacent keys, e.g.“zxcv” and also non-adjacent, e.g. “axml” or “axnk” or “axbj.”

Maintaining a finite, non-zero error rate is an aspect of the invention.Subjects are instructed to maintain responses within a limited range oferror. A minimum error rate must be maintained. For each 20 keystrokes,the minimum number of errors should be at least three fewer than themaximum number of errors. Preferably, the lower error rate is 2 errorsper 20 keystrokes and the upper error rate is 5 errors per 20keystrokes. It is acceptable that the lower error rate is as high as 5errors per 20 keystrokes and the upper error rate be 10 errors per 20keystrokes so long as the upper bound differs from the lower by at least3 errors per 20 keystrokes. The method will tolerate a wide range oferror, and in fact, examinees are encourage to remain within aconsistent and narrow range—choosing their own comfortable upper andlower limits so long as their upper and lower limits are 3 errors apart.

Step 2: Collect Health and Health Habit Information.

Instructions are displayed to the examinee directing the input ofcertain health and habit information. Collecting this type ofinformation before testing begins is critical since test results mayoften bias self-perceived health and distort results. The information iscollected to allow subsequent analysis of relationships between healthhabits, non-cognitive health and cognitive health that may allow usersto adjust their habits to maximize both cognitive fitness and overallhealth. Health information has been collected prior to testing butnever, to my knowledge, as a regular part of repeated testing to enablehealth and cognitive fitness to be optimized. Regular collection of bothcognitive performance and health/health habit information is essentialfor statistical analysis of correlations between each, to determine ifchanges in health behavior precede changes in cognitive performance. Theregular collection of health/health habit information as part of eachmeasurement session is thus an aspect of the present inventivemeasurement system.

Step 3: Cache all Signals for Rapid Presentation.

“Caching” in the sense used here is the transmission of data for signalsor stimuli to be presented (e.g., images of the numbers 0 through 9,letters, sounds, etc.) via the DDS, for example the Internet, fortemporary storage on each DNE computer accessing the performancemeasurement web site (SNE). Delays in Internet transmission make itimpossible to rapidly present signals without advance caching. And rapidpresentation of signals is essential for precise response timemeasurement. If signals are not presented substantially instantaneously,then users will respond prematurely, or have their responses biased,when they see ⅛, ¼, ⅓, ½ (etc.) of a multi-part challenge signal as itis gradually displayed.

Prior art web sites require users to download and set up performancetests on their own computers, a long and arduous task that I believemost users will not complete, or else the sites use code-generatedchanges in background color that severely limit the possible range ofchallenge signals which can be employed.

Step 4: Set all Parameters to Initial Values.

Parameters are variables used in the program. Initializing variables forpast results (response time and error rates) allows users to viewconstantly updated comparisons between past performance and presentperformance, and to adjust present performance to equal or improve onpast results. In an alternative embodiment such comparisons are madeduring delays or breaks. In a preferred embodiment, parameterinitialization allows for setting user expectations at the beginning ofeach session allows for more rapid and complete adjustment during theinitial set of responses.

Step 5: Trans Form Prior Results.

Prior results are transformed into key descriptors like average,standard deviation, etc. for most convenient and understandablecomparisons with results obtained during the present measurementsession.

Step 6: Calibrate the Measurement Accuracy of Each Computer (DNE) BeforeEach and Every Response.

Users should not waste their time obtaining unreliable results simplybecause they computer is not measuring their response time accurately.Inaccuracy may be due to very temporary interference from other programshidden in the “background”. To detect such interference, a series ofcommands is executed and the time required for these commands to becompleted is measured. If the difference between the expected executiontime and the actual execution time (the measurement error) is too large,measurement is halted and a warning appears, advising the user of theproblem. Whether the measurement error is acceptable or not, it isstored for comparisons with error in future sessions, and an average foreach series of responses is computed and displayed so users can seeimmediately if slight interference has occurred even if the limit ofacceptability has not been exceeded.

Step 7: Determine Acceptability of Measurement Precision.

The limits of acceptability should be sufficiently small to preventstatistically significant errors from occurring. Since typical usersvary from day to day by up to 10%, a measurement error rate of 10% orless for each keystroke is acceptable provided that errors areconsistently in one direction or are randomly high or low, and providedthat the percentage error has been determined over a time period roughlyequivalent to the time period required for a typical response. In otherwords the error in response time measurement should roughly correspondto the error in computer measurement for the following error analysis tobe valid. Errors of 10% may seem unacceptably high however if 20 sucherrors are averaged they generally almost completely cancel, if errorsare randomly high and low, resulting in an error of 0.5% or less. Ifmeasurement errors are consistently high across measurement sessions,then the change in response time between sessions will also not beaffected by measurement error if errors are consistently high. Forexample, if user A requires an average of 35 centiseconds to respond onMonday, but the computer records 38.5% due to a 10% average measurementerror, and if user A returns on Tuesday and averages 35.5% with the samemeasurement error of 10%, then his average on Tuesday will be 35.5×1.1or 39.05. The observed change from Monday to Tuesday will be 39.05−38.5or 0.55 centiseconds. The actual change was 0.5 seconds, so there was ameasurement error of 0.05 centiseconds or only 0.14% of the averageresponse time (0.05/35.5×100=0.14%) even with a 10% measurement error.Since only changes of 10% or greater are outside the normal day-to-daychange, indicating perhaps the start of an adverse drug reaction or alarge benefit from additional vitamin E consumed on previous days, anerror of only 0.14% can certainly be ignored since it is only oneseventieth as large as changes commonly encountered.

Some scientists may dismiss use of personal computers for accurateresponse time measurement because millisecond errors occur intransmission of keystrokes from keyboard to the computer. Such tinyerrors are too large for these scientists to tolerate. Excessive concernabout such minute errors may be one reason why response timemeasurements are not more widely investigated or used for healthbenefits. Given large day-to-day variations commonly encountered whenusers measure their response time over weeks, months and years, concernabout errors so much smaller than actually observed changes seeminappropriate.

For these reasons, I believe the best cutoff point for acceptable erroris relatively high (10%). Setting a high acceptability cutoff preventsusers from encountering error warnings during every test session—aninconvenience that may add to the time and irritation associated withmeasurement and reduce use of the system, preventing fewer patient-usersfrom monitoring potentially life-saving improvements or life-threateningdecrements in their performance.

To ensure that errors do in fact cancel across measurement sessions,average errors for consecutive sessions must not change by over 2% orwarnings are generated advising that measurement errors be more tightlycontrolled.

Step 8: Display Accuracy Warning.

Where a measurement accuracy warning is generated, users are advised toclose other programs, to check that the change from each session to thenext is less than 2%, or to call a webmaster or measurement advisor foradditional assistance reducing measurement errors.

Step 9: Select the Signal to be Presented.

To allow repeated use of the measurement site, challenge signalspresented to the user must be different during each response series,random numbers are used to select from among possible challenge signals.As used herein, the term challenge signal may refer to a singlecharacter, for example the numeral “1”. However, the term challengesignal may refer to a sequence of characters, for example the string“371.”

Step 10: Is the Signal the Same as the Previous Signal?

The term response refers to keystroke(s) and/or mouse clicks made byexamine following presentation of a challenge signal. For example, wherethe numeral “1” is displayed, a keystroke corresponding to the numeral“2” would represent an incorrect response, while a keystrokecorresponding to the numeral “1” represents a correct response. Whenpreparing to response, nerve and muscle cells may be “primed” or readyto respond more rapidly where an identical challenge signal is presentedseveral times in sequence. Therefore, signal repetition is to beminimized. It is also important to prevent alert users from anticipatinga changed challenge signal where it is known signal repetition is notpermitted. In a three-choice response time test, for example, if a 1 ispresented then the user may expect a 2 or a 3, knowing 1 cannot occuragain, so the number of choices is reduced from 3 to 2, causing the testto be in effect a two-choice response time test, which has different andin some respects less desirable properties in comparison with athree-choice test. Preventing repetition is particularly important fornumber recall tests, during which users who cannot remember whether a 5or 6 was used in position 4 of a 5 digit sequence may reason that thecorrect answer is 6 because the third digit was 5 and the 5 could nothave been repeated. To rule out anticipation and reasoning of this kind,the probability that a signal is repeated is reduced by three fourths(using random numbers to determine whether repetition is allowed eachtime) so that the effects of repeated numbers, anticipation andreasoning as described are all muted.

Step 11: “Softshift” the Signal.

As used herein the term softshifting refers to the procedure to adjustchallenge signals that violate rules governing permitted challengesignal sequences. Initially a random challenge signal is generated andtested to determine whether the challenge signal so generated violates asignal sequence restriction rule. Where the challenge signal has beendetermined to violate a sequence restriction rule, a softshiftadjustment procedure is invoked. Softshifting comprises the steps of (a)generating a random test number, (b) comparing the random test number toa pre-set threshold number, (c) where the random test number is greaterthan the threshold number, generate and display an alternative randomchallenge signal. Where the test number is less than the thresholdnumber, display the original challenge signal. The invention is notlimited to a specific softshift algorithm. The critical feature is tochange the challenge signal, some of the time, but not every time, saidchallenge signal violates signal sequence restrictions.

If a signal is repeated, or an element of a multi-component signal isrepeated, a random number is selected to indicate whether repetition ispermitted in this instance. There is no “hard” rule that repetition isforbidden. There is only a “soft” rule, with regular exceptions, thatindicates a change is required most of the time. If this random numberindicates that a change must occur, the signal is shifted to anequivalent alternative, perhaps to a number one larger than the originalsignal or to a symbol selected at random. This process is called a“softshift.” Its purpose is to prevent the examinee from counting signaloccurrences, trying to outguess and anticipate the signal selectionsystem, and being distracted and having their performance affected byguessing while signals are being presented.

Step 12: Has the Signal Been Selected too Often?

Random choices of signals sometimes will cause one signal to be selectedwithin a series significantly more often than others, distorting averageresponse time or recall results, increasing between-series standarddeviations and reducing the level of confidence possible for any changesobserved. To prevent this from occurring, a limit is placed on thenumber of times each signal can be selected during each series—howeverthe limit is a soft limit, allowing exceptions, to discourage signalcounting and anticipation that frequently-used signals cannot be usedagain (similar to card counting).

Step 13: Has the Difference Between the Selected Signal and the PreviousSignal Occurred too Often During the Current Series?

Where challenge signals increase by some number, for example 1, twice ina row, a similar change may be anticipated, affecting response time orrecall accuracy. A soft limit is therefore placed on the occurrence ofidentical changes between consecutive signals and also within a seriesof signals. Changes may involve consecutive responses with the left orright hand, or involve responses with index and middle fingers. Duringrecall measurements, this type of limit reduces the likelihood of serieslike 2, 3, 4 or 4, 6, 8 or 3, 6, 9 or corresponding descending series,or series like 1,3,1,3 or 8,4,8,4 or red green red green that can beeasily remembered and may enable longer-than-usual numbers to berecalled. Such series can be recognized by testing to determine whether(i) the difference between consecutive numeric signals is the same, (ii)a signal is the same as the signal to slots previously and the previoussignal is also the same as the signal two slots before said previoussignal

Step 14: Determine Whether the Current Challenge Signal in Combinationwith Previous Signals Form a Forbidden Series.

Occurrence of a leading zero as the first digit of a series, or of a oneand a nine as the first two digits of a series, may enable number seriesto be recalled more easily and distort recall measurements. (19 . . .can be recalled as a year like 1945 or 1963 if linked with verymemorable events like the end of WW II or Kennedy's assassination.) Toreduce the frequency of such distortion, specific series can be detectedand their occurrence subjected to softshifting so they are less frequentand distortion is reduced.

Step 15: Cache the Challenge Signal and the Frequency that the Signalhas been Presented.

This is an essential part of signal balancing (ensuring approximatelyequal numbers of each possible signal in each series).

Step 16: Select the Delay Prior to Signal Presentation.

Many response time tests incorporate a variable delay before signalpresentation to prevent anticipation of when presentation will occur andtherefore prevent a response prior to signal presentation. Randomnumbers are used to control the delay time to avoid obvious patterns.Long intermediate and short delays can be counted and subjected tofrequency limits as described above

Step 17: Determine Accuracy of Computer Response During the Delay Priorto Presentation of Each Signal.

In a preferred embodiment of the present invention the accuracy ofcomputer response is determined during the delay prior to presentationof each signal.

Step 18: Present the Signal from a Local Cache.

In a preferred embodiment of the present invention, image and soundfiles, used to generate challenge signals, are cached in the DNE localmemory. Local caching allows for substantially instantaneous retrievaland presentation.

Step 19: Measure Start Time.

In a preferred embodiment, the response time is measured after thechallenge signal has been presented. In the preferred embodiment, thechallenge signal is generated, and where necessary, softshifted. Thepresentation delay time is generated, and where necessary, softshifted.Following expiration of the delay time, the challenge signal ispresented and the response start time determined and cached.

Step 20:Eliminate Active Commands During Dwell Period.

In a preferred embodiment, essentially immediately upon presentation ofa challenge signal, keystroke capture mode is activated so that the nextkeystroke activates subsequent steps. In order that there be minimalinterference with keystroke capture commands, it is essential that noother computations, other than background environment chores beyondbrowser or RSMMS control, be performed during the dwell period. In apreferred embodiment of the present invention, keystroke-capturesoftware and precise control of active and inactive periods are used sothat other keystrokes are not misinterpreted as responses.

Step 21. Capture the Response Keystroke and Determine the Response Time.

In a preferred embodiment, both the symbol encoded by a responsivekeystroke (or mouse click) and the elapsed time following presentationof the challenge signal are captured. It is preferred that the responsetime is determined prior to the execution of any other commands. In apreferred embodiment, the response and response time are cached forlater analysis.

Step 22: Determine Whether Response is a Command.

In a preferred embodiment, certain keystrokes are interpreted ascommands. For example, where the letter “b” is pressed, the program isset to recognize that the user wishes to take a break and the responseis not counted. Other commands can conveniently be inserted here. Caremust be taken not to allow commands that may distract users andinfluence subsequent responses.

Step 23: Execute the Command.

Care must be taken that executing commands input at step 22 does notstart processes that may continue and interfere with subsequentmeasurement accuracy. For example, other windows must not be opened andleft open since the burden of window management will change and theadditional interference may cause computer response time measurementerrors.

Step 24: Is the Response Time too High or Low?

Lucky responses occasionally occur when users start pressing the correctkey even before a signal has been presented. Responses below a thresholdare discarded. In an embodiment of he invention, the threshold is set at10 centiseconds. Distractions may also cause unusually long responsesthat are also discarded. The longest permitted response for athree-choice or four-choice response time measurement system should beabout 2 seconds for older users or users with health conditions thatdelay response time, and should be 1 second for younger, faster users.Thresholds for other response time tests must be chosen specifically foreach test.

Step 25: Display Response Time Out-of-Bounds Message.

It is important to indicate to users whether response times are out ofbounds so they can learn how long to wait before pressing subsequentkeys if they are temporarily distracted for any reason or if they presskeys only partly and wish to have the response ignored rather thancaptured as an unusually slow response or incorrect response. In anembodiment of the invention, users simply wait for 2 seconds then pressthe correct key to continue signal presentation for the rest of theseries. No time is recorded if users wait longer than the upper limitfor responses set in set 24.

Step 26: Is the Response Correct?

In an embodiment of the invention, incorrect responses are captured sothat error patterns can subsequently be analyzed, however in a preferredembodiment, incorrect responses do not count toward the total number of(correct) responses required for each series of responses. It istherefore necessary to detect incorrect responses and make certain thecorresponding response times are not used to compute the current seriesaverage, and to decrease the response counter so that the correct numberof accurate responses are collected during the current series.

Step 27: Display the Incorrect Response Image and Increase the IncorrectResponse Counter.

Responses are collected so rapidly that it is often difficult for usersto realize when they perform incorrect responses. Recognizing errors isof course essential for maintaining an error rate above a lower limitand below an upper limit, so a brightly colored message is displayedwithin the signal presentation area (where it cannot be missed) to alertusers each time an error is made.

Step 28: Is the Error Rate Among Recent Responses Over a Threshold?

Users often hit bad streaks where responses correspond to previousrather than current signals, or for other reasons a run of errors aremade. In a preferred embodiment of the invention, users are helped to“snap out” of these error streaks. A message is displayed and testing isinterrupted where excessive (e.g. more than 4) errors are made withinthe preceding 5 to 10 responses. Use of “error-cluster buster”mini-breaks is an aspect of a preferred embodiment.

Step 29: Display a “Take a Break” Message.

Where excessive errors are detected during step 28, a preferredembodiment invokes a routine to advise users to “take a moment towriggle your fingers. Then press OK to continue.”

Step 30: Increment the Correct Response Counter.

It is important for users to see how many responses they have made ineach series, and how many errors, to determine whether their currenterror rate is acceptable, or whether more or fewer errors should bemade. It is therefore important not only to increment the responsecounter after each response, but also to display the result clearly.

Step 31: Compute and Display the Average Response Time and OtherIndicators of Error Rates and Computer Measurement Accuracy.

In a preferred embodiment of the invention, the average response timeand other indicators of error rates and computer measurement accuracyare computed and displayed after each keystroke. This must be done aftereach keystroke if users are to be able to adjust within each series ofresponses to maintain or exceed speed and accuracy levels achieved inthe past.

Step 32: Is the Average or Score for the Most Recent Series Much Higheror Lower Than the Previous Average?

If there is a large difference between the current and the precedingresult, a notice pops up advising the user of the change, so that theycan determine if the change is reproducible by completing additionalseries, and if yes so that can take appropriate action. A preferredembodiment calculates differences between scores achieved betweenconsecutive response series within each measurement session

Step 33: Display a Message Related to the Observed Change in Score orAverage.

Where a decline in health status is observed and confirmed by additionalmeasurement, extra cautious driving or a call to a professional healthadvisor may be appropriate. Where improved health status is noted,additional health habit adjustments to enhance the improvement may beappropriate, again after checking with a professional health advisor. Apreferred embodiment displays appropriate motivational messages relatedto improvements or declines in health status, as determined byvariations between consecutive response series within a measurementsession.

Step 34: Is the Total Number of Responses During the Current SeriesEqual to the Limit for the Series?

Where, for example, 20 of 20 desired correct responses have beenobtained during the 25 current series, then the series is over andadditional reports are prepared while the user has a small rest period.If fewer than 20 correct responses have been obtained, then the programloops back to step 6 to obtain the required responses.

Step 35: Increment the Series Counter.

Counting the number of series is important because users occasionallylose track of how many series they have performed. Reminding them mayhelp prevent over-testing, eyestrain and mental fatigue that willdiscourage the repeated testing so critical for long-term measurementaccuracy.

36. Compute a “Cleaned” Average, Standard Deviation, Split Half ErrorRate and Other Measures of Response Speed and Accuracy and ComputerMeasurement Accuracy.

In a preferred embodiment, a cleaned average is computed. In a preferredembodiment, a cleaned average of response is determined excluding valuesfor the fastest and slowest responses. Since on average moreslower-than-average responses occur compared to faster-than-averageresponses, more slow responses are rejected in each series than fastresponses.

In a preferred embodiment a “split half” average is determined.Determination of the difference between the average of odd responsesminus the average of even responses ( e.g., the average response time ofresponses 1, 3, 5, 7, 9, 11, 13, 15, 17 and 19 minus the average ofresponses 2, 4, 6, 8, 10, 12, 14, 16, 18 and 20) allows speedfluctuations due to second-by-second changes in mental fatigue, eyestrain, motivation to respond rapidly or accurately, etc. to be canceledsince both averages are affected more or less proportionately. If thepercentage difference between these odd/even split half averages is toohigh, then the results of the series may be too inconsistent foraccuracy and a message pops up advising the user to perform anotherseries or contain an adviser to determine what is causing the split halferror rate to be higher than acceptable.

A preferred embodiment for memory evaluation purposes defines a scorefor any measurement session as longest series recalled n-timesconsecutively. Where n is some pre-determined integer, for example 2 or3. In an embodiment score is defined as the average of the fastest nconsecutive response series. Where such an n-series score is determined,the score should be updated and displayed so users can see clearly wherethey stand compared to previous results.

37. Store all Results.

If the accuracy and speed of present results are to be compared withfuture results, with adjustment for variations in computer measurementaccuracy, each data set must be stored for future retrieval andcomparison. No other Internet or non-Internet RSMMS currently storesinformation in packets that include the signal, the response, theresponse time and the computer measurement accuracy result obtained justbefore signal presentation, so storage of this type of data packet istherefore claimed as a unique feature of this invention.

If space is limiting and more compact storage is necessary, then onlyseries response time averages, total errors per series, and the averageof computer measurement accuracy for each series need be stored.Information packets with these three items of information are alsoclaimed to be unique features of the RSMMS being patented.

Step 38: Is the Most Recent Series of Results Acceptable?

In a preferred embodiment, an acceptable series is defined as, forexample, the number of errors being within pre-defined bounds; and/orthe split half error less than a threshold value; and/or computermeasurement errors less than a pre-determined threshold. Where resultsare unacceptable, a warning is displayed recommending that the series berepeated.

Step 39. Display Appropriate Message if Data are Acceptable.

It is important to give users encouragement and a pat on the back forwork well done, to add some fun to the process so they will be morelikely to return for follow-up measurements and build a more accuratedata set, add to their own understanding of connections between theirpersonal health habits and cognitive performance, and also add to ageneral body of understanding that may benefit many others. Giving usersa pat on the back several times with each measurement session concerningseveral independent measures of data acceptability is to my knowledgeunique to this RSMMS and is therefore claimed as a unique feature ofthis invention.

Step 40. Display Appropriate Message if Data are Borderline Unacceptableor Acceptable.

Suggest repeating the last series, perhaps reducing interruptions thatcause attention to lapse, or calling an advisor to discuss persistentproblems with data acceptability. Giving users messages concerning howto improve several independent measures of data acceptability is to myknowledge unique to this RSMMS and is therefore claimed as a uniquefeature of this invention.

Step 41. Is the Series Total Prior to Comprehensive Graphing andEvaluation Equal to the Required (Upper or Lower) Limit?

A graph of prior and current results can be prepared after each seriesof responses, or after every two, three, four or five series. If thenumber of series completed equals the limit needed for graphing, thenthe graph and associated analysis should be prepared. The best value forthis limit is simply 1, since graph preparation then gives users a breakafter each series has been completed and reduces between-series fatigueand (proactive) interference. This step is not a unique feature of thisRSSM system and is only claimed as part of a unique combination offeatures comprising the invention being patented.

Step 42. Save, then Initialize Within Series Counters.

After each series is complete, the total errors, average response timeand average computer measurement error must be stored for future use andthe values must be initialized so the next series begins from zero or novalue for each measure of performance determined by each series ofresponses. This step is not a unique feature of this RSSM system and isonly claimed as part of a unique combination of features comprising theinvention being patented.

Step 43. Display a Graph of Previous Results.

After each series or several series, graphing results allows users tosee at a glance if their current responses are worse, better or the sameas previous responses. Response time and error rates should bepresented, or health or health habit data should be displayed for easyexamination. Giving users graphs of both past and present results is tomy knowledge unique to this RSMMS and is therefore claimed as a uniquefeature of this invention.

Step 44. Display the Standard Deviation or Other Measures of Variabilityfor Recent Averages.

It is best to display measures of between series variability along withthe graph of past and present results so that users can see thevariability at a glance and decide whether additional data should beobtained. Controlling measures of between-series variability (e.g.minimizing the standard deviation among the most recent 5 series of 20responses) allows users to monitor and possibly control factors thatoperate over many series, just as measures of within-series variation(e.g. the standard deviation within results from one series of 20responses) allows users to monitor and possibly control factors thatoperate within each series, like very short term changes inconcentration or interruptions from background noise or occasionalinterference from background computer programs. Giving users measures ofvariation that span both past and present results is to my knowledgeunique to this RSMMS and is therefore claimed as a unique feature ofthis invention.

Steps 45, 46 and 47. Are Measures of Variability Among Recent (Past asWell as Present) Series Averages Acceptable?

If not, display appropriate messages as in steps 38-40. Since factorsthat affect past vs. present results operate over much longer timeperiods compared to factors that cause variation within a series (i.e.within a ten- to 15-second period), it is appropriate to mentionpossible causes of between-session variation like changes in the amountof exercise or sleep from day to day which can be minimized for moreconsistent cognitive performance. Giving users messages concerningvariation across both past and present results is to my knowledge uniqueto this RSMMS and is therefore claimed as a unique feature of thisinvention.

Step 48. Analyze Probability that Recent Results are or are notSignificantly Different from Previous Results.

To major goals of statistical analysis are to determine whether a steadybaseline has been obtained before a health supplement, dietary change ormedication is tried, and to determine whether changes observed after achange has been made are in fact statistically significant or perhapsare simply part of normal, random variation. Both kinds of statisticaltests are provided on the RSMMS web site for visitors to convenientlyuse.

Baseline adequacy is determine by a t-test for paired data performed todetermine whether recent results will be statistically different fromequivalent results (with roughly the same standard deviation) if achange of 1%, 3% or 6% occurs. Data pairing for the “paired” t-test isbased on order of series averages within each measurement session: e.g.,the first series result on Monday is paired with the first on Tuesday,the second series result on Monday is paired with the second on Tuesday,etc., so that the effects of progressive fatigue and warm-up over theseries within each measurement session can be canceled to some degree.

A paired t-test for the most recent n series vs. the previous n seriesis also available (where n is selected by the user) to determine ifrecent series are significantly different from the preceding series.

And a multiple t-test “Search for Significance” performs paired t-testson the most recent 3, 4, 5 . . . and preceding 3, 4, 5 . . . seriesaverages (until the end of stored data is reached) and reports anysignificant changes (above a cutoff provided by the user).

The ready availability of significance tests for baseline adequacy andevaluation of observed change is to my knowledge unique to this RSMMSand is therefore claimed as a unique feature of this invention.

Steps 49, 50, 51, 52, 53. Prepare Easy-to-Understand Confidence Levelsfor Display and E-Mailing along with Appropriate Messages.

Most users are not statisticians, so a percentage confidence in anyobserved change is computed from the p values generated by the t-testequations. Percent confidence=(1−pvalue)×100. A plain English statementabout the degree of confidence is prepared, displayed and also storedfor automatic or manual e-mailing. Preparation of easy-to-understandstatistical reports based on percent confidence is to my knowledgeunique to this RSMMS and is therefore claimed as a unique feature ofthis invention. Preparation of easy-to-understand reports for e-mailingto health advisors or personal health data centers is to my knowledgeunique to this RSMMS and is therefore claimed as a unique feature ofthis invention.

Two kinds of “confidence history” are also available at the web site,where “confidence history” means a listing of confidence levels that themost recent 3 results are significantly different from the previous 3,that the last 4 are significantly different from the previous 4, thatthe last 5 are . . . up to the highest number permitted by storedresults—or that the most recent n results (n=3, 4, 5 . . . ) aresignificantly different from the previous n, that the n resultsbeginning with the 2nd-most-recent-result are significantly differentfrom the preceding n results, that the n results beginning with the3rd-most-recent-result are significantly different from the preceding nresults . . . back to the start of the data set.

The following sample output illustrates the kind of results obtained bya preferred embodiment of the present inventive RSMMS:

Your response time average was 32.83±3.2% (20 correct/5 incorrect).

Your odd/even ratio for this set of 20 was 1.016.

Computer measurement errors averaged 0.13%.

Please consult a health professional before interpreting these results.

Response Time Table for Visitor

09/22/1999 06:55:05 Response Time Bar chart Date/hr/min/sec (and healthratings) [Not shown]  1) 09/15/1999 10:10:55 29.63 (2/3)  2) 09/15/199910:28:14 31.61  3) 09/15/1999 10:29:02 30.82  4) 09/15/1999 10:29:5930.24  5) 09/15/1999 10:31:16 28.8  6) 09/16/1999 08:36:30 30.83 (3/3) 7) 09/16/1999 08:37:19 30.63 (3/3)  8) 09/16/1999 08:38:47 31.66 (3/3) 9) 09/16/1999 08:39:57 31.83 (3/3) 10) 09/16/1999 08:41:32 31.61 (3/3)11) 09/17/1999 10:40:48 30.48 (4/3) 12) 09/17/1999 10:42:03 29.43 (4/3)13) 09/17/1999 10:47:24 29.86 (4/3) 14) 09/17/1999 10:48:29 30.85 (4/3)15) 09/17/1999 10:49:38 29.24 (4/3) 16) 09/18/1999 10:29:20 29.24 (2/1)17) 09/18/1999 10:30:34 31.41 (2/1) 18) 09/18/1999 10:31:42 32.01 (2/1)19) 09/18/1999 10:32:51 31.83 (2/1) 20) 09/18/1999 10:33:48 31.83 (2/1)21) 09/19/1999 09:20:57 31.85 (3/2) 22) 09/19/1999 09:22:42 30.02 (3/2)23) 09/19/1999 09:24:11 31.46 (3/2) 24) 09/19/1999 09:25:29 32.23 (3/2)25) 09/19/1999 09:26:39 31.5 (3/2) 26) 09/21/1999 09:01:51 29.26 (3/3)27) 09/21/1999 09:03:15 32.04 (3/3) 28) 09/21/1999 09:04:22 29.66 (3/3)29) 09/21/1999 09:05:26 31.41 (3/3) 30) 09/21/1999 09:06:41 31.05 (3/3)31) 09/22/1999 06:49:07 28.82 (2/2) 32) 09/22/1999 06:50:42 28.26 (2/2)33) 09/22/1999 06:52:32 30.05 (2/2) 34) 09/22/1999 06:53:49 33.05 (2/2)Most recent result: 32.83 (2/2)

Please keep a separate record of these results in case your data“cookie” is erased.

To print these results, click on File and Print.

Avg for last 5 visits: 30.60±7.29%. SDev is good.

Data cache: 1017 bytes out of 4,000.

Baseline confidence analysis: The ratio of your first 17 to your second17 response times is 30.48/30.96 or 0.984. This ratio is notsignificantly different from 1.00 according to a split-half t test forpaired data. It thus appears that you have obtained stable baselinedata.

If you obtain the same amount of data during the next month and youraverage is shifted by 1%, then the observed change will be significantat a confidence level of 89.21%. If the shift is 3%, then yourconfidence level will be 99.8%. And f the shift is 6% or 15% yourconfidence will be 99.9% or 99.9%.

Significance Test: The ratio of the previous 10 response times to yourmost recent 10 is 31.33/30.64 or 1.022 (confidence=91.7%). Your mostrecent 10 results appear to be significantly different from the previous10 results. Please send this report to your professional health advisorif you wish to discuss changes in your medication or supplements. Note:Due to rounding and interpolation errors, calculated levels ofsignificance are approximate. If you have questions about thisstatistical test, please send today's results to VitaminEstudy@go.com.Be sure to include your E-mail address for a reply.

Significance Report:

The ratio of the previous 8 response times to your most recent 8 is31.27/30.64 or 1.020 (confidence=74.8%).

The ratio of the previous 9 response times to your most recent 9 is31.22/30.79 or 1.017 (confidence=76.2%).

The ratio of the previous 10 response times to your most recent 10 is31.33/30.64 or 1.022 (confidence=91.7%).

The ratio of the previous 11 response times to your most recent 11 is31.08/30.72 or 1.011 (confidence=73.0%).

The ratio of the previous 16 response times to your most recent 16 is30.62/30.95 or 0.989 (confidence=82.7%).

The ratio of the previous 17 response times to your most recent 17 is30.62/31.00 or 0.987 (confidence=87.4%).

To send your results to a physician, pharmacist or other health advisor,enter their E-mail address in the space below. Then enter your codename, E-mail, phone number or other information they require on the nextline.

Send my results to this E-mail address: [input box]

My code name, E-mail, phone or other info: [input box]

Remarks: [input box]

[Send button]

[Return to Measurement Page button]

[End of sample output]

According to a preferred embodiment of the invention, the examinee isoffered the option to prepare ratings for each food, supplement,medicine, health habit or other factor, listed by the examinee, toindicate which are associated with improvement or decrement in examineeperformance. The result of this calculation is a complete or partiallist of all health factors mentioned (during step 2) prior toperformance measurement and an associated score for each item on thelist (e.g. a positive number indicating the degree to which performanceimprovements occurred afterward, or a negative number indicating thatperformance was poorer afterward). Partial lists would include the top n(e.g. 10) foods, etc. and the worst n (e.g. 10) foods, etc. The value ofpartial lists is that most of the statistically insignificantbenefit/decrement values are omitted. The key to this benefit-decrementrating is relatively precise time-date information for both healthfactors and performance results, and dose and frequency-of-useinformation for health factors whenever possible or convenient.Time-date and dose information allows the relative degree of associationbetween each factor and performance results to be adjusting in much thesame way the inventor believe collections of nerve cells formconnections between potentially related events or discharge patterns.The benefit-decrement calculation algorithm is simply to determine thechange in performance (after vs. before each factor exerted possibleinfluence), add up all these changes for each factor, weight themagnitude of the associations according to the difference in timebetween performance measurement and the health factor, and also weightthe magnitude of each association according to cumulative dose if doseinformation is available. Weights for each food, medicine and otherhealth factor need not be the same. Associations may be weakened by thesimultaneous presence of several of the health factors under evaluation.Further description of the benefit-decrement calculation algorithm isprovided by the “optimization” code provided below.

Sample Output Obtained from a Preferred Embodiment of the Invention

Items listed first appear to raise the selected health measure.Food/beverage Rating EGGS 3 ORANGE-JUICE 3 TEA 1.5 APPLES 1.28 BREAD1.28 OATMEAL 0 MILK 0

Items listed last appear to lower the selected health measure.

Send Email copy to: [Email address box, with previous addressautomatically recalled]

[End of sample output]

Importance of Health Data/Performance Data/Benefit-Decrement Reports:

The direct linked between measurement precision and combined collectionof health habit/food data and performance data and preparation ofbenefit-decrement reports should be emphasized. RSMMS users who do notsee relatively rapid results linked with documented benefits will notreturn to obtain the additional data that enables more precisemeasurement averages to be determined.

How to Make the Invention:

According to a preferred embodiment of the invention, computer code forInternet and non-Internet embodiments are provided. Some sections willrun without adaptation if the following instructions are followed,however other sections (e.g. those involving the CGI code) requirecomputer specific directories and/or Internet locations to be inserted.Those persons of reasonable skill in the programming arts willunderstand from the present disclosure how to adapt the code to a givencomputer environment.

The computer code supplied is illustrative of a preferred embodiment.The computer code should not limit in any way the scope of the claimssince it represents only one implementation of the more general methodsclaimed.

1) Type or copy into a text-format file the HTML and JavaScript code (orequivalent code) for each web page provided below and save each pageunder the exact file name provided in the page title (or other filenames provided that every page name reference in the code has beenchanged accordingly) on the c: drive of a Windows 95, 98, NT orequivalent computer system.

2) Change the action commands for each form (<FORM . . . ACTION=specifya database or e-mail address here>) in each of these HTML files tospecify a database or e-mail address to which data can be sent—or elsedisable all submit commands.

3) Prepare or copy images of the following or equivalent images and savethem under the names indicated below on a Windows 95, 98, NT orequivalent computer system. Signal images to be displayed prior to eachresponse can be prepared at the exact height, width, color and design ofimages available at the inventor's web site (to be listed on majorsearch engines under the key words Response Speed and Memory MeasurementSystem after this patent has been approved) however different sizes,colors and designs can also be employed.

Required Images Include:

-   -   Images of the permitted challenge signals. Said images may        comprise the numbers 0 to 9 and/or other signal images,        depending on the signals desired;    -   An image indicating that the previous response was incorrect;    -   An image requesting that the user “please wait” for scheduled        feedback to be prepared and displayed;    -   A blank image to be displayed before the program starts;    -   An image showing proper finger placement during each response        series, for the instruction page. This finger-placement image        may be different for each test within the RSSM system, and may        not be needed for some tests, like number and word recall, for        which specific finger placement is not required.

Unless the code for each page is adjusted, images should be named:

-   num0.gif-   num1.gif-   num2.gif-   num3.gif-   num4.gif-   num5.gif-   num6.gif-   num7.gif-   num8.gif-   num9.gif-   numBlank.gif-   numEnd.gif-   numError.gif-   numwait.gif

Site specific images and images explaining different measurement optionsfor the main entrance page can be named as indicated below. In thefollowing non-limiting embodiment, letters represent the following: chsis for Connecticut Healthspan System (a system for increasing eachperson's span of healthy years, as well as lifespan)—these lettersidentify all image-links in the central area of a general access pagelinking to all measurement options currently hidden beneath the choiceresponse time measurement page; jts—join the study—the image that linksto a description of vitamin and herb study options; srt—simple reactiontime, a response time test that has just one signal and one response(very simple); crt—choice reaction time, a response time test with 2, 3,4 or more signals and a different response for each; pet—planning andexecution time, a relatively complex response time test that involvesplanning and execution of a series of responses to each signal; ms—mathspeed; stm—short-term memory, for numbers; mss—memory scanning speed;hr—health report—this image links to a page that allows daily, weekly .. . health reports to be filed on-line.

For Links to a Tour of the Site:

-   Tour.gif-   Tour2.gif    For Descriptions of Each Measurement Option:-   chsBlankText.gif-   chsJtsText.gif-   chsStudiesText.gif-   chsHR1Text.gif-   chsSrtText.gif-   chsCrtText.gif—for Response time-   chsPetText.gif-   chsMsText.gif-   chsMssText.gif-   chsStmText.gif

For image-links to each measurement option (if you click on each image,the web browser opens the corresponding measurement page):

-   chsjts1.gif-   chssrt.gif-   chscrt.gif—for Response time-   chspet.gif-   chsms.gif-   chsmss.gif-   chsstm.gif-   chsjts2.gif-   chssrt2.gif-   chscrt2.gif-   chspet2.gif-   chsms2.gif-   chsmss2.gif-   chsstm2.gif-   chshr11.gif-   chshr12.gif    Optional Sounds Include:

Four or more sound files in .wav format are recommended. These soundfiles can be any sounds desired, each to trigger 1 or a combination ofresponses, but should be short segments to avoid unnecessary delay andannoyance while the signal sound is completed. If only simple auditoryresponse time is to be measured, then just a single sound file isneeded. Note: To reduce downloading time, sound options are not includedin Refcrt22.htm so a different version, Refcrt21.htm, is also includedbelow for those who wish to adapt the trimmed version to include soundsignals. This version also contains softshift code for reducing repeatsignals, etc.

Sound File Names are:

-   sound0.wav-   sound1.wav-   sound2.wav-   sound3.wav-   sound4.wav-   sound5.wav-   sound6.wav-   sound7.wav-   sound8.wav-   sound9.wav

Of course these and all other image and variable names can be changed toequivalent, more descriptive names.

It will, therefore, be appreciated by those skilled in the art havingthe benefit of this disclosure that this invention is capable ofproducing A computer based system for testing the cognitive performanceof at least one examinee. Although the illustrative embodiments of theinvention are drawn from the internet arts, the invention is notintrinsically limited to that art. Furthermore, it is to be understoodthat the form of the invention shown and described is to be taken aspresently preferred embodiments. Various modifications and changes maybe made to each and every processing step as would be obvious to aperson skilled in the art having the benefit of this disclosure. It isintended that the following claims be interpreted to embrace all suchmodifications and changes and, accordingly, the specification anddrawings are to be regarded in an illustrative rather than a restrictivesense. Moreover, it is intended that the appended claims be construed toinclude alternative embodiments.

Appendix

Program code for a preferred embodiment is included as a floppy diskappendix. Said disk is formatted for Windows 98 operating system and thefile is in Word 98 format.

1-116. (canceled)
 117. A computer based method for testing the cognitiveperformance of at least one examinee comprising; providing to at leastone examinee at least one measurement-session comprising a plurality ofresponse-series comprising a plurality of responses; and providing acomputer-generated instruction that said examinee respond rapidly to atest stimulus so that at least a minimum number of errors is made: 118.The computer based method for testing the cognitive performance of atleast one exaninee, according to claim 117, wherein said instruction isprovided prior to a response-series.
 119. The computer based method fortesting the cognitive performance of at least one examinee, according toclaim 117, further comprising: determining a number of errors made bysaid examinee in a response-series; and displaying a computer-generatedinstruction to increase a response speed of said examinee when saidnumber of errors is less than a minimum number of errors within saidresponse-series.
 120. The computer based method for testing thecognitive performance of at least one examinee, according to claim 117,wherein said response-series comprises from about 15 to about 30responses.
 121. The computer based method for testing the cognitiveperformance of at least one examinee, according to claim 117, whereinsaid minimum number of errors is an integer selected from the groupconsisting of 1,2,3,4, and
 5. 122. The computer based method for testingthe cognitive performance of at least one examinee, according to claim117, wherein said minimum number of errors is from about 10% to about20% of said responses.
 123. The computer-based method for measuring thecognitive performance of at least one examinee, according to claim 117,further comprising displaying a warning message when a response-seriesincludes less than said minimum number of errors, wherein said warninginstructs said examinee to proceed more rapidly during remainingresponse-series within said measurement-session.
 124. A computer basedmethod for testing the cognitive performance of at least one examineecomprising: reading at least one word input by an examinee; determininga performance score by said examinee; and correlating said score withsaid at least one health-related word.
 125. The computer based methodfor testing the cognitive performance of at least one examinee,according to claim 124, further comprising: ranking said words by amagnitude of change of said performance score after input of said word.126. The computer based method for testing the cognitive performance ofat least one examinee, according to claim 124, further comprising:determining at least one time period after input of said word;correlating said word and performance in said at least one time period.127. The computer based method for testing the cognitive performance ofat least one examinee, according to claim 124, further comprising:displaying a list of words input by said examinee; and displaying foreach said word a correlation between said word and a change of saidperformance score for said examinee.
 128. The computer based method formeasuring the cognitive performance of at least one examinee, accordingto claim 126, wherein said correlation comprises a function including atime differential between an input of a word and a performance score.129. The computer-based method for measuring the cognitive performanceof at least one examinee, according to claim 125, further comprising:providing said examinee with a list of words rated by their correlationwith positive changes in performance; and providing said examinee anexplanation that words given highest ratings are most likely torepresent beneficial foods and other health-related items.
 130. Thecomputer-based method for measuring the cognitive performance of atleast one examinee, according to claim 124, further comprising:providing said examinee with means to obtain a health rating for anyword entered at the time of measurement.
 131. The computer-based methodfor measuring the cognitive performance of at least one examinee,according to claim 124, further comprising: providing first and secondhealth ratings for each said word; and providing said examinee withmeans to obtain each said first and second healthy ratings.
 132. Thecomputer-based method for measuring the cognitive performance of atleast one examinee, according to claim 124, further comprising:providing said examinee with means to search for said entered words withthe highest and lowest health ratings.
 133. The computer-based methodfor measuring the cognitive performance of at least one examinee,according to claim 123, further comprising: providing said examinee withmeans to obtain a health rating for any word combination byconcatenating words within the combination.
 134. A computer-based methodfor word analysis comprising: providing a user with means to obtain aranking of at least one previously-input word; and ranking said at leastone word by a health or performance change subsequent to said input.135. The computer-based method for word analysis, according to claim134, wherein said at least one word is selected from the group of wordsconsisting words describing health-factors, performance factors, andcognitive factors.
 136. The computer-based method for measuring thecognitive performance of at least one examinee, according to claim 134,further comprising: providing said examinee with means to select atime-period covered by the analysis.